A metric-based heuristic framework to detect object-oriented design flaws

被引:24
|
作者
Salehie, Mazeiar [1 ]
Li, Shimin [1 ]
Tahvildari, Ladan [1 ]
机构
[1] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
关键词
D O I
10.1109/ICPC.2006.6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the important activities in re-engineering process is detecting design flaws. Such design flaws prevent an efficient maintenance, and further development of a system. This research proposes a novel metric-based heuristic framework to detect and locate object-oriented design flaws from the source code. It is accomplished by evaluating design quality of an object-oriented system through quantifying deviations from good design heuristics and principles. While design flaws can occur at any level, the proposed approach assesses the design quality of internal and external structure of a system at the class level which is the most fundamental level of a system. In a nutshell, design flaws are detected and located systematically in two phases using a generic OO design knowledge-base. In the first phase, hot spots are detected by primitive classifiers via measuring metrics indicating a design feature (e.g. complexity). In the second phase, individual design flaws will be detected by composite classifiers using a proper set of metrics. We have chosen JBoss Application Server as the case study, due to its pure OO large size structure, and its success as an open source JMEpla form among developers.
引用
收藏
页码:159 / +
页数:2
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